Objects: We collect objects from four popular asset repositories – Amazon Berkeley Objects [1]}, Google Scanned Objects [2]}, ReplicaCAD [3]}, and YCB Objects [4]}. We filter out objects with large dimensions (e.g. ladders, televisions), and objects that do not usually move in a household (e.g. garbage cans). After filtering, we have 1799 unique objects spread across 268 categories. We further categorize these objects into 19 high-level semantic categories such as stationery, food, electronics, toys, etc. More details about the filtering, semantic classes, and high/low-level object categories are in the Appendix .
